Oil financialization and volatility forecast: Evidence from multidimensional predictors

Using the generalized dynamic factor model, this study constructs three predictors of crude oil price volatility: a fundamental (physical) predictor, a financial predictor, and a macroeconomic uncertainty predictor. Moreover, an event‐triggered predictor is constructed using data extracted from Google Trends. We construct GARCH‐MIDAS (generalized autoregressive conditional heteroskedasticity–mixed‐data sampling) models combining realized volatility with the predictors to predict oil price volatility at different forecasting horizons. We then identify the predictive power of the realized volatility and the predictors by the model confidence set (MCS) test. The findings show that, among the four indexes, the financial predictor has the most predictive power for crude oil volatility, which provides strong evidence that financialization has been the key determinant of crude oil price behavior since the 2008 global financial crisis. In addition, the fundamental predictor, followed by the financial predictor, effectively forecasts crude oil price volatility in the long‐run forecasting horizons. Our findings indicate that the different predictors can provide distinct predictive information at the different horizons given the specific market situation. These findings have useful implications for market traders in terms of managing crude oil price risk.     

Nowcasting with Google Trends in an Emerging Market

Most economic variables are released with a lag, making it difficult for policy‐makers to make an accurate assessment of current conditions. This paper explores whether observing Internet browsing habits can inform practitioners about aggregate consumer behavior in an emerging market. Using data on Google search queries, we introduce an index of online interest in automobile purchases in Chile and test whether it improves the fit and efficiency of nowcasting models for automobile sales. Despite relatively low rates of Internet usage among the population, we find that models incorporating our Google Trends Automotive Index outperform benchmark specifications in both in‐sample and out‐of‐sample nowcasts, provide substantial gains in information delivery times, and are better at identifying turning points in the sales data. Copyright © 2011 John Wiley & Sons, Ltd.     

Twisting the Dollar? On the Consistency of Short‐Run and Long‐Run Exchange Rate Expectations

We examine consistency properties of the exchange rate expectation formation process of short‐run and long‐run forecasts in the dollar/euro and yen/dollar market. Applying nonlinear consistency restrictions we show that in a simple expectation formation structure short‐run forecasts are indeed inconsistent with long‐run predictions. Moreover, we establish a ‘twist’ in the dollar/euro expectation formation process, i.e. market participants expect bandwagon effects in the short run, while they have stabilizing expectations in their long‐run forecasts. Applying a panel probit analysis we find that this twisting behavior is more likely to occur in periods of excess exchange rate volatility. Copyright © 2011 John Wiley & Sons, Ltd.     

Predicting Recessions with Factor Linear Dynamic Harmonic Regressions

We propose a new framework for building composite leading indicators for the Spanish economy using monthly targeted predictors and small‐scale dynamic factor models. Our leading indicator index, based on the low‐frequency components of four monthly economic variables, is able to predict the onset of the Spanish recessions as well as the gross domestic product (GDP) growth cycles and classical industrial production cycles, both historically and in real time. Also, our leading indicator provides substantial aid in forecasting annual and quarterly GDP growth rates. Using only real data available at the beginning of each forecast period, our indicator one‐step‐ahead forecasts shows substantial improvements over other alternatives. Copyright © 2013 John Wiley & Sons, Ltd.     

International Evidence on GFC‐Robust Forecasts for Risk Management under the Basel Accord

A risk management strategy designed to be robust to the global financial crisis (GFC), in the sense of selecting a value‐at‐risk (VaR) forecast that combines the forecasts of different VaR models, was proposed by McAleer and coworkers in 2010. The robust forecast is based on the median of the point VaR forecasts of a set of conditional volatility models. Such a risk management strategy is robust to the GFC in the sense that, while maintaining the same risk management strategy before, during and after a financial crisis, it will lead to comparatively low daily capital charges and violation penalties for the entire period. This paper presents evidence to support the claim that the median point forecast of VaR is generally GFC robust. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria. In the empirical analysis we choose several major indexes, namely French CAC, German DAX, US Dow Jones, UK FTSE100, Hong Kong Hang Seng, Spanish Ibex 35, Japanese Nikkei, Swiss SMI and US S&P 500. The GARCH, EGARCH, GJR and RiskMetrics models as well as several other strategies, are used in the comparison. Backtesting is performed on each of these indexes using the Basel II Accord regulations for 2008–10 to examine the performance of the median strategy in terms of the number of violations and daily capital charges, among other criteria. The median is shown to be a profitable and safe strategy for risk management, both in calm and turbulent periods, as it provides a reasonable number of violations and daily capital charges. The median also performs well when both total losses and the asymmetric linear tick loss function are considered Copyright © 2012 John Wiley & Sons, Ltd.     

On a robust test for SETAR‐type nonlinearity in time series analysis

There has been growing interest in exploiting potential forecast gains from the nonlinear structure of self‐exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR‐type nonlinearities in observed time series. However, previous studies show that classical nonlinearity tests are not robust to additive outliers. In practice, time series outliers are not uncommonly encountered. It is important to develop a more robust test for SETAR‐type nonlinearity in time series analysis and forecasting. In this paper we propose a new robust nonlinearity test and the asymptotic null distribution of the test statistic is derived. A Monte Carlo experiment is carried out to compare the power of the proposed test with other existing tests under the influence of time series outliers. The effects of additive outliers on nonlinearity tests with misspecification of the autoregressive order are also studied. The results indicate that the proposed method is preferable to the classical tests when the observations are contaminated with outliers. Finally, we provide illustrative examples by applying the statistical tests to three real datasets. Copyright © 2009 John Wiley & Sons, Ltd.     

On the association between IPO underpricing and reversal and Taiwan's regulatory reforms for mandatory forecasts

The unique institutions in Taiwan may add to our understanding of the effect of initial public offering (IPO) firm disclosures. Consistent with the notion of market mispricing, most of Taiwan's IPOs were with consecutive up‐limit hits followed by substantial price reversals. In this study, we decompose IPO underpricing into two components: pure underpricing and subsequent reversal, exploring the impact of the 1991 mandate that IPO firms should include their management forecasts in the prospectuses on these two anomaly measures. Our results support the notion that disclosure regulations ameliorate investors' mispricing the stocks. First, pure underpricing and reversal are significantly less (more) pronounced for post‐mandate (pre‐mandate) IPO stocks. In contrast, consistent with the cheap talk hypothesis, the pre‐mandate voluntary forecasters (non‐forecasters) appear to be more (less) underpriced. Second, the duration of underpricing for the post‐mandate (pre‐mandate) IPOs appears to be shorter (longer). Nevertheless, underpricing lasted relatively longer (shorter) for the pre‐mandate IPOs with (with no) voluntary disclosures. Copyright © 2009 John Wiley & Sons, Ltd.     

Modelling the frequency and severity of extreme exchange rate returns

Risk managers are often concerned about tail probabilities of asset return distributions, in particular the frequency and severity of extreme returns. In this article, we propose a model that integrates extreme value theory and point processes to model the frequency and severity of exchange rate returns. The proposed model is applied to daily spot exchange rate series and the parameters of interest, such as the tail index, the mean size and rate of occurrence of extreme returns, are estimated using maximum likelihood estimation. We study the impact of recent currency crises on the frequency and severity of the series and find that, during 1995–9, the frequency of extreme daily Japanese yen–US dollar spot exchange rate returns increases twofold, and the time duration of high volatility persists longer for the Japanese yen series than for the Swiss franc and Danish krone series. Copyright © 2001 John Wiley & Sons, Ltd.     

Glass behaviour: Poisson's ratio and liquid's fragility

The lack of a reliable theory of glass physics has led to the pursuit of correlations between various glass or viscous liquid parameters, one of which is the slope m of the plot of log(viscosity) against Tg/T, extrapolated at the glass-transition temperature, Tg, also termed 'fragility'. Novikov and Sokolov conclude that the value of m for a liquid varies linearly with the ratio of the instantaneous bulk and shear moduli, K infinity/G infinity, of its glass according to the relation m=29(K infinity/G infinity -0.41). Because of the obvious importance of the elastic properties of a glass, we have investigated the basis for this relation and find that its premise is flawed because of the unjustifiable preference for an empirical variation of m with elastic properties, and because of the selected use of glasses. When more glasses are considered in the same way, m does not seem to be linearly related to K infinity/G infinity.